saturn

/home/coolhand/servers/diachronica/corpus/historical-corpora/pceec/data/aif_2022.csv 4,970 rows sample n=4,970 seed 42 2026-05-01T17:52:28+00:00

Overview

Source/home/coolhand/servers/diachronica/corpus/historical-corpora/pceec/data/aif_2022.csv
Total rows4,970
Profiled sample4,970
Columns13
Generated2026-05-01T17:52:28+00:00

Insights opt-in

Model-generated narrative. These are opinions, not facts — the stats below are what saturn measured. Generated by: anthropic:claude-opus-4-7.

Errors during insight pass (14)
  • dataset:__global__:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuXJVmCPk7uBUa9ueW'}
  • column:Letter reference:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuXnmXan5QcAZYpx2q'}
  • column:Author name:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuYgqodWpucUQJSHyu'}
  • column:Author API:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuZJYv3giXFnjQQqyX'}
  • column:Author gender:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuaRmYu5kkBqCSenFD'}
  • column:Author DOB:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGubJrF4nqAZpuZxdcg'}
  • column:Relation to recipient:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuboceLp4qXV7B5KSf'}
  • column:Recipient:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGucEAeEWCq7FDrUo3F'}
  • column:Recipient API:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGud2nZdZ5ebT2gAkAz'}
  • column:Recipient gender:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGudYnVgkL6FFxMNKAV'}
  • column:Recipient DOB:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGue5HZaLcKAoyaaCH5'}
  • column:Relation to author:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGueaoDBR4Nks1uFMxB'}
  • column:Change from 2006?:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGuf3aVLfhE5dY9DqYp'}
  • column:Order of Gardiner letters in file:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacGufS9VKWUvGBnG6ZKM'}

Letter reference text

100.0% of rows are unique strings 100.0% rows are a single word 100.0% rows are all-caps 95th-percentile length under 20 chars
rows4,970
null0 (0.0%)
unique4,970
len_min7
len_max11
len_mean10.092
len_median10.000
len_p9511.000
word_mean1.000
word_median1.000
n_empty0
n_duplicates0
duplicate_rate0.000
vocab_size4,970
readability_flesch_mean49.310
emoji_rate0.000
url_rate0.000
one_word_rate1.000
allcaps_rate1.000
boilerplate_rate0.000
Sample values (first 10)
  1. ARUNDEL_003
  2. PASTON_337
  3. RERUM_019
  4. PEPYS_078
  5. HAMILTO_005
  6. WENTWOR_001
  7. HARLEY_074
  8. SMYTH_020
  9. PETTY_010
  10. BACON_092

Author name categorical

rows4,970
null0 (0.0%)
unique695
top_valueJOHN_HOLLES_SR
top_rate0.027
cardinality695
entropy8.192
entropy_ratio0.868
Top values (rank 1–20)
  1. JOHN_HOLLES_SR — 136
  2. THOMAS_CROMWELL — 93
  3. DOROTHY_OSBORNE/TEMPLE — 85
  4. NATHANIEL_BACON_I — 77
  5. JOHN_CHAMBERLAIN — 71
  6. THOMAS_WENTWORTH — 67
  7. MARGARET_PASTON[N.MAUTBY] — 66
  8. ARABELLA_STUART — 65
  9. BRILLIANA_HARLEY[N.CONWAY] — 61
  10. STEPHEN_GARDINER — 58
  11. SAMUEL_PEPYS — 58
  12. JOHN_PARKHURST — 55
  13. JOHN_JONES — 53
  14. ANTHONY_ANTONIE — 51
  15. ROBERT_DUDLEY — 47
  16. KATHERINE_PASTON[N.KNYVETT] — 47
  17. RICHARD_CELY_JR — 46
  18. WILLIAM_CECIL — 45
  19. THOMAS_KNYVETT — 45
  20. THOMAS_HOWARD_III — 44

Author API categorical

25.0% null
rows4,970
null1,244 (25.0%)
unique252
top_valueSIR
top_rate0.150
cardinality252
entropy6.060
entropy_ratio0.760
Top values (rank 1–20)
  1. SIR — 560
  2. LADY — 278
  3. MERCHANT — 149
  4. KING_OF_ENGLAND — 140
  5. 1ST_EARL_OF_CLARE/POLITICIAN(DNB) — 136
  6. BISHOP_OF_WINCHESTER — 111
  7. CLERK — 103
  8. EARL_OF_ESSEX/ROYAL_MINISTER(DNB) — 93
  9. SIR/LOCAL_POLITICIAN(DNB) — 79
  10. BISHOP_OF_NORWICH — 77
  11. 1ST_EARL_OF_STRAFFORD/LORD_LIEUTENANT_OF_IRELAND — 67
  12. PUBLIC_SERVANT — 58
  13. COLONEL — 55
  14. 1ST_LORD_BURGHLEY/ROYAL_MINISTER(DNB) — 48
  15. EARL_OF_LEICESTER/COURTIER/MAGNATE(DNB) — 47
  16. 2ND_EARL_OF_ARUNDEL_AND_SURREY/POLITICIAN(DNB) — 44
  17. 3RD_EARL_OF_DERBY — 40
  18. SIR/NATURAL_PHILOSOPHER/ADMINISTRATOR(DNB) — 40
  19. SIR/2ND_BART/SCHOLAR/POLITICIAN(DNB) — 38
  20. SIR/LORD_CHANCELLOR(DNB) — 38

Author gender categorical

rows4,970
null0 (0.0%)
unique2
top_valueMALE
top_rate0.831
cardinality2
entropy0.655
entropy_ratio0.655
Top values (rank 1–20)
  1. MALE — 4,130
  2. FEMALE — 840

Author DOB categorical

31.2% null
rows4,970
null1,549 (31.2%)
unique217
top_value1565?
top_rate0.040
cardinality217
entropy6.746
entropy_ratio0.869
Top values (rank 1–20)
  1. 1565? — 136
  2. 1546? — 120
  3. 1633 — 99
  4. 1485? — 97
  5. 1627 — 85
  6. 1593 — 79
  7. 1533 — 79
  8. 1585 — 73
  9. 1554 — 71
  10. 1575 — 66
  11. 1600? — 61
  12. 1623 — 60
  13. 1497? — 58
  14. 1631 — 55
  15. 1511 — 55
  16. 1596 — 53
  17. 1597? — 53
  18. 1442 — 52
  19. 1614 — 50
  20. 1608 — 48

Relation to recipient categorical

44.4% null
rows4,970
null2,205 (44.4%)
unique45
top_valueFRIEND
top_rate0.140
cardinality45
entropy4.211
entropy_ratio0.767
Top values (rank 1–20)
  1. FRIEND — 387
  2. BROTHER — 353
  3. SON — 250
  4. KIN — 187
  5. BROTHER-IN-LAW — 169
  6. MOTHER — 162
  7. HUSBAND — 160
  8. FATHER — 149
  9. FAMILY_SERVANT — 140
  10. WIFE — 126
  11. COUSIN — 115
  12. SON-IN-LAW — 93
  13. FUTURE_WIFE — 78
  14. DAUGHTER — 47
  15. NEPHEW — 47
  16. SISTER-IN-LAW — 42
  17. SISTER — 38
  18. NIECE — 37
  19. FATHER-IN-LAW — 29
  20. UNCLE — 26

Recipient categorical

317 singleton categories
rows4,970
null0 (0.0%)
unique623
top_valueJOHN_PASTON_I
top_rate0.053
cardinality623
entropy7.351
entropy_ratio0.792
Top values (rank 1–20)
  1. JOHN_PASTON_I — 262
  2. NATHANIEL_BACON_I — 251
  3. JOAN_BARRINGTON — 182
  4. JANE_CORNWALLIS/BACON[N.MEAUTYS] — 180
  5. GEORGE_CELY — 119
  6. HENRY_OXINDEN[BARHAM] — 107
  7. DANIEL_FLEMING — 100
  8. ROBERT_PLUMPTON_I — 87
  9. WILLIAM_TEMPLE — 85
  10. JOHN_PASTON_III — 84
  11. WILLIAM_STONOR — 81
  12. THOMAS_LANGLEY — 75
  13. THOMAS_STOCKWELL — 73
  14. THOMAS_WOLSEY — 65
  15. EDWARD_HARLEY — 64
  16. HENRY_CLIFFORD_II — 63
  17. CHRISTOPHER_HATTON_III — 63
  18. HENRY_TUDOR_VIII — 57
  19. JOHN_PASTON_II — 56
  20. MARGARET_PASTON[N.MAUTBY] — 50

Recipient API categorical

rows4,970
null940 (18.9%)
unique326
top_valueSIR
top_rate0.134
cardinality326
entropy6.128
entropy_ratio0.734
Top values (rank 1–20)
  1. SIR — 542
  2. LADY — 444
  3. SIR/LOCAL_POLITICIAN(DNB) — 253
  4. MERCHANT — 154
  5. SIR/ANTIQUARY — 100
  6. BARONET/DIPLOMAT/AUTHOR(DNB) — 85
  7. SIR/MERCHANT — 82
  8. BISHOP_OF_DURHAM/LORD_CHANCELLOR — 75
  9. ROYAL_MINISTER/ARCHBISHOP_OF_YORK/CARDINAL(DNB) — 71
  10. KING_OF_ENGLAND — 68
  11. BISHOP_OF_WINCHESTER — 68
  12. 1ST_EARL_OF_CUMBERLAND — 64
  13. VISCOUNT — 63
  14. BISHOP_OF_DURHAM — 59
  15. CAPTAIN — 55
  16. EARL_OF_LEICESTER/COURTIER/MAGNATE(DNB) — 49
  17. SIR/PRINCIPLE_SECRETARY(DNB) — 45
  18. VISCOUNTESS — 45
  19. SIR/LORD_KEEPER_OF_THE_GREAT_SEAL — 43
  20. VISCOUNT_DORCHESTER/DIPLOMNAT(DNB) — 43

Recipient gender categorical

rows4,970
null0 (0.0%)
unique3
top_valueMALE
top_rate0.820
cardinality3
entropy0.688
entropy_ratio0.434
Top values (rank 1–20)
  1. MALE — 4,074
  2. FEMALE — 892
  3. MALE/FEMALE — 4

Recipient DOB categorical

rows4,970
null975 (19.6%)
unique210
top_value1421
top_rate0.066
cardinality210
entropy6.310
entropy_ratio0.818
Top values (rank 1–20)
  1. 1421 — 264
  2. 1546? — 256
  3. 1581 — 185
  4. 1558? — 182
  5. 1633 — 140
  6. 1608 — 108
  7. 1628 — 90
  8. 1453 — 88
  9. 1444 — 86
  10. 1449? — 82
  11. 1360? — 75
  12. 1595 — 71
  13. 1473? — 65
  14. 1632? — 64
  15. 1624 — 64
  16. 1631 — 62
  17. 1644 — 61
  18. 1493? — 61
  19. 1533 — 57
  20. 1491 — 57

Relation to author categorical

46.2% null
rows4,970
null2,297 (46.2%)
unique43
top_valueFRIEND
top_rate0.145
cardinality43
entropy4.127
entropy_ratio0.761
Top values (rank 1–20)
  1. FRIEND — 387
  2. BROTHER — 324
  3. SON — 295
  4. BROTHER-IN-LAW — 192
  5. KIN — 188
  6. WIFE — 160
  7. MOTHER — 160
  8. FATHER — 138
  9. HUSBAND — 126
  10. COUSIN — 115
  11. MOTHER-IN-LAW — 81
  12. FUTURE_HUSBAND — 78
  13. SISTER — 67
  14. UNCLE — 59
  15. FAMILY_SERVANT — 53
  16. FATHER-IN-LAW — 43
  17. NEPHEW — 29
  18. SON-IN-LAW — 27
  19. SISTER-IN-LAW — 26
  20. AUNT — 25

Change from 2006? categorical

top value is 95.5% of rows
rows4,970
null0 (0.0%)
unique4
top_valueok
top_rate0.955
cardinality4
entropy0.303
entropy_ratio0.151
Top values (rank 1–20)
  1. ok — 4,746
  2. corrected — 175
  3. corrected in spreadsheet — 46
  4. ok sic — 3

Order of Gardiner letters in file numeric

98.8% null
rows4,970
null4,912 (98.8%)
unique58
min1.000
max58.000
mean29.500
median29.500
std16.887
q115.250
q343.750
iqr28.500
skew0.000
kurtosis-1.201
n_outliers0
outlier_rate0.000
zero_rate0.000